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承德市大气污染源排放清单及典型行业对PM2.5的影响
引用本文:陈国磊,周颖,程水源,杨孝文,王晓琦.承德市大气污染源排放清单及典型行业对PM2.5的影响[J].环境科学,2016,37(11):4069-4079.
作者姓名:陈国磊  周颖  程水源  杨孝文  王晓琦
作者单位:北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124,北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124,北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124,北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124,北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124
基金项目:国家自然科学基金项目(91544232,51638001);国家环境保护公益性行业科研专项(201409006);北京市科技计划项目(Z141100001014002)
摘    要:以承德市为研究对象,基于拉网式实地调查,获得了该地区2013年各类典型行业污染源详细的活动水平数据,以大气污染物排放清单编制指南为参考,辅以排放因子研究的系统梳理,建立了2013年承德市各行业区县分辨率大气污染源排放清单,并结合人口、路网、土地利用等数据进行了1 km×1 km网格分配.在此基础上建立气象-空气质量模型系统(WRFCAMx),应用颗粒物来源识别技术(PSAT),选取2013年典型季节代表月1、4、7、10月,针对承德市电力、建材、冶金等典型行业对PM_(2.5)的影响进行了定量评估.结果表明,2013年承德市SO_2、NO_x、TSP、PM_(10)、PM_(2.5)、CO、VOCs、NH_3的总排放量分别为81 134、72 556、368 750、119 974、51 152、1 281 371、170 642、81 742 t.工业源是SO_2、NO_x、CO、VOCs的主要排放源,分别占总排放量的89.5%、51.9%、82.5%和45.6%,NO_x的主要排放源还包括道路移动源和非道路移动源,分别占总排放量的26.7%和10.8%;TSP、PM_(10)、PM_(2.5)的主要排放源是无组织扬尘,分别占总排放量的76.7%、65.6%、46.5%;畜禽养殖、化肥施用是NH_3的主要排放源,分别占总排放量的67.1%、15.8%.数值模拟结果表明,无组织扬尘、其他行业、冶金、锅炉行业对环境PM_(2.5)影响较大,浓度贡献分别为23.1%、20.6%、13.3%和11.2%,制定具体控制措施时应得到重点关注.

关 键 词:排放清单  承德  空间分布  CAMx-PSAT  PM2.5
收稿时间:2016/5/13 0:00:00
修稿时间:2016/6/16 0:00:00

Air Pollutant Emission Inventory and Impact of Typical Industries on PM2.5 in Chengde
CHEN Guo-lei,ZHOU Ying,CHENG Shui-yuan,YANG Xiao-wen and WANG Xiao-qi.Air Pollutant Emission Inventory and Impact of Typical Industries on PM2.5 in Chengde[J].Chinese Journal of Environmental Science,2016,37(11):4069-4079.
Authors:CHEN Guo-lei  ZHOU Ying  CHENG Shui-yuan  YANG Xiao-wen and WANG Xiao-qi
Institution:Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China,Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China,Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China,Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China and Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China
Abstract:In this study, detailed activity level of typical sector in Chengde in 2013 was obtained through a full-coverage investigation. A comprehensive emission inventory with country-level resolution in 2013 was developed based on guide of atmospheric pollutant emission inventory and updated emission factors. Then, the emission inventory within 1 km×1 km grid was generated using source-based spastial surrogates including population, road network and landuse date. Furthemore, meteorology-air quality modeling system (WRF-CMAx) including Particulate Source Apportionment Technology (PSAT) module was established in order to evaluate the impact of topical sector (e. g., electric power, the production of construction materials, the metallurgical industry, etc.) on PM2.5 concentration in January, April, July and October which were considered as the representative months of winter, spring, summer and autumn. The results showed the total emission of SO2, NOx, TSP, PM10, PM2.5, CO, VOCs and NH3 in Chengde in 2013 was respectively 81134 t, 72556 t, 368750 t, 119974 t, 51152 t, 1281371 t, 170642 t and 81742 t. Industrial source was the main emission contributor of SO2, NOx, CO, VOCs, accounting for 89.5%, 51.9%, 82.5% and 45.6% of total emissions, respectively. The major emission source of NOx also included on-road and non-road mobile source, respectively accounting for 26.7% and 10.8%. The major emission source of TSP, PM10 and PM2.5 was fugitive dust, accounting for 76.7%, 65.6% and 46.54%, respectively. Ammonia emissions from animals and farm accounted for 67.1% and 15.8% of total emissions, respectively. The numerical simulation result showed that the fugitive dust, the others, the metallurgical industry and boilers industry had relatively higher contributions to PM2.5 concentration, accounting for 23.1%, 20.6%, 13.3% and 11.2%, respectively. These emission sources should be paid more attention during the decision-making with respect to control strategies.
Keywords:emission inventory  Chengde  spatial allocation  CAMx-PSAT  PM2  5
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